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MTRX5700: Experimental Robotics (2019 - Semester 1)

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Unit: MTRX5700: Experimental Robotics (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Postgraduate
Faculty/School: School of Aerospace, Mechanical & Mechatronic Engineering
Unit Coordinator/s: Prof Williams, Stefan
Session options: Semester 1
Versions for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: (AMME3500 OR AMME9501 OR AMME8501) AND MTRX3700.
Brief Handbook Description: This unit aims to present a broad overview of the technologies associated with industrial and mobile robots. Major topics covered are sensing, mapping, navigation and control of mobile robots and kinematics and control of industrial robots. The subject consists of a series of lectures on robot fundamentals and case studies on practical robot systems. Material covered in lectures is illustrated through experimental laboratory assignments. The objective of the course is to provide students with the essential skills necessary to be able to develop robotic systems for practical applications.

At the end of this unit students will: be familiar with sensor technologies relevant to robotic systems; understand conventions used in robot kinematics and dynamics; understand the dynamics of mobile robotic systems and how they are modeled; have implemented navigation, sensing and control algorithms on a practical robotic system; apply a systematic approach to the design process for robotic systems; understand the practical application of robotic systems in manufacturing, automobile systems and assembly systems; develop the capacity to think critically and independently about new design problems; undertake independent research and analysis and to think creatively about engineering problems.

Course content will include: history and philosophy of robotics; hardware components and subsystems; robot kinematics and dynamics; sensors, measurements and perception; robotic architectures, multiple robot systems; localization, navigation and obstacle avoidance, robot planning; robot learning; robot vision and vision processing.
Assumed Knowledge: Knowledge of statics and dynamics, rotation matrices, programming and some electronic and mechanical design experience is assumed.
Lecturer/s: Dr Ila, Viorela
Prof Williams, Stefan
Tutor/s: Jasper Brown (j.brown@acfr.usyd.edu.au) and Max Revay (m.revay@acfr.usyd.edu.au)
Timetable: MTRX5700 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Independent Study 5.00 13
2 Laboratory 3.00 1 13
3 Lecture 2.00 1 13
T&L Activities: Laboratory: Material covered in lectures is illustrated through experimental laboratory assignments. By applying the techniques they have learned, students will be given the opportunity to contextualize their learning. Application of the concepts will encourage a deeper approach to their learning. Labs will be conducted once a week in the Mechatronics Lab.

Lecture: The series of lectures will cover robot fundamentals and case studies examining practical robot systems. Experts in the field will be invited to present guest lectures to give the students a broad exposure to robotic systems both in research and industrial contexts.

Attributes listed here represent the key course goals (see Course Map tab) designated for this unit. The list below describes how these attributes are developed through practice in the unit. See Learning Outcomes and Assessment tabs for details of how these attributes are assessed.

Attribute Development Method Attribute Developed
Select and apply appropriate mathematical and programming techniques as part of the design labs. (1) Maths/ Science Methods and Tools (Level 4)
Students will gain an overview of the technologies associated with industrial and mobile robots. (2) Engineering/ IT Specialisation (Level 5)
Design and conduct experiments and to analyse and interpret data from those experiments. (4) Design (Level 4)
Effective communication techniques that emphasize clear and concise presentation of ideas, concepts and solutions to both technical and non-technical audiences.
Collate a variety of information sources within the engineering discipline including technical books and reports, research articles and requirements documents.
(6) Communication and Inquiry/ Research (Level 3)
Develop a commitment to, and fundamental appreciation of, the concept of successful teamwork. (7) Project and Team Skills (Level 3)

For explanation of attributes and levels see Engineering & IT Graduate Outcomes Table 2018.

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

(6) Communication and Inquiry/ Research (Level 3)
1. Ability to express ideas both orally and written on technical material. Students will present the outcomes of their major project to their peers and staff through a presentation and demonstration. A report outlining the relevant background, design and outcomes will also be prepared.
(4) Design (Level 4)
2. Apply a systematic approach to the design process for robotic systems. Students will gain an understanding of the components that make up a robotic system and will have the opportunity to exercise these skills on a major project of their choosing.
(2) Engineering/ IT Specialisation (Level 5)
3. Examine advanced topics in robotics including obstacle avoidance, path planning, robot architectures, multi-robot systems and learning as applied to robotic systems. Students will have the opportunity to examine these topics in more detail as part of their major project.
4. Be familiar with sensor technologies relevant to robotic systems. Specifically work with laser and vision data and examine techniques for processing this data. Techniques for identifying features, such as lines within laser data and corners in visual data, will be examined
5. Have implemented navigation, sensing and control algorithms on a practical robotic system. Examine methods for fusing multiple data sources to improve a navigation solution. Using the navigation solution, students will also examine mapping techniques used in mobile robotic systems.
6. Understand conventions used in robot kinematics and dynamics. In particular, methods for assigning frames of reference to robotic systems and techniques for transforming between frames will be described. Students will apply these methods to the study of manipulator and mobile robotic systems.
(3) Problem Solving and Inventiveness (Level 4)
7. Develop the capacity to think creatively and independently about new design problems.
8. Undertake independent research and analysis and to think creatively about engineering problems.
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Assignment 1 Yes 10.00 Week 4 (Wednesday) 1, 4, 6, 7,
2 Assignment 2 Yes 10.00 Week 6 (Wednesday) 1, 4, 6, 7,
3 Assignment 3 Yes 10.00 Week 9 (Wednesday) 1, 5, 7, 8,
4 Major Project Yes 40.00 Week 13 1, 2, 3, 4, 5, 6, 7, 8,
5 Final Exam No 30.00 Exam Period 3, 4, 5, 6, 7,
Assessment Description: Assignment: Labs will be conducted once a week. The use of laboratory work will allow students to apply their newfound knowledge of robotic systems to a variety of practical systems. The introductory labs are designed to familiarize students with the material required to prepare for the major laboratory project. Introductory Labs (30%) Consist of 1. Manipulator Lab: Due Week 4 (10%); 2. Sensing Lab: Due Week 6 (10%); 3. Navigation Lab: Due Week 9 (10%)

Assignment: Major Project Presentation and Report - Students will be asked to present a demonstration of their major project to other students and staff. This will encourage them to produce a system of sufficient quality that they can demonstrate it to their peers. This will also provide the students with an opportunity to share their experiences with their classmates.

Final Exam: A final exam will test students` understanding of course material.
Grading:
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at http://sydney.edu.au/policies . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Policies & Procedures: See the policies page of the faculty website at http://sydney.edu.au/engineering/student-policies/ for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.
Recommended Reference/s: Note: References are provided for guidance purposes only. Students are advised to consult these books in the university library. Purchase is not required.
Note on Resources: There is no prescribed text for this course. Recommended reading and references will be provided in relation to assignments. Lectures etc available on eLearning (webCT)

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp

Week Description
Week 1 Introduction, history and philosophy of robotics.
Week 2 Lecture: Robot kinematics & dynamics
Lab: Kinematics/Dynamics
Week 3 Lecture: Sensors, measurements and perception
Lab: Kinematics/Dynamics
Week 4 Lecture: Robot vision and vision processing.
Lab: Sensing
Assessment Due: Assignment 1
Week 5 Lecture: Localization and navigation.
Lab: Sensing
Week 6 Lecture: Extra Tutorial Session - Sensing lab demo
Lab: Robot Navigation
Assessment Due: Assignment 2
Week 7 Lecture: Estimation and Data Fusion
Lab: Robot navigation
Week 8 Lecture: Obstacle avoidance and path planning
Lab: No Lab - Good Friday
Week 9 Lecture: Extra tutorial session (nav demo)
Lab: Major project
Assessment Due: Assignment 3
Week 10 Lecture: Robotic architectures, multiple robot systems
Lab: Major project
Week 11 Lecture: Robot learning
Lab: Major project
Week 12 Lecture: Case Study
Lab: Major project
Week 13 Lecture: Extral tutorial (Major project)
Lab: Major Project demonstration.
Assessment Due: Major Project
Exam Period Assessment Due: Final Exam

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Biomedical Engineering / Law 2013, 2014
Biomedical Engineering / Arts 2013, 2014
Biomedical Engineering / Commerce 2013, 2014
Biomedical Engineering / Medical Science 2013, 2014
Biomedical Engineering / Project Management 2013, 2014
Biomedical Engineering / Science 2013, 2014
Biomedical - Chemical and Biomolecular Major 2013, 2014, 2015
Biomedical - Electrical Major 2013, 2014
Biomedical - Information Technology Major 2013, 2014, 2015
Biomedical - Mechanical Major 2013, 2014, 2015
Biomedical - Mechatronics Major 2013, 2014, 2015
Biomedical Mid-Year 2016, 2017, 2018, 2019, 2020
Biomedical/ Project Management 2019, 2020
Biomedical 2016, 2017, 2018, 2019, 2020
Biomedical / Arts 2015, 2016, 2017, 2018, 2019, 2020
Biomedical / Commerce 2015, 2016, 2017, 2018, 2019, 2020
Biomedical / Medical Science 2015, 2016, 2017
Biomedical / Music Studies 2016, 2017
Biomedical / Project Management 2015, 2016, 2017, 2018
Biomedical /Science 2015, 2016, 2017, 2018, 2019, 2020
Biomedical/Science (Health) 2018, 2019, 2020
Biomedical - Electrical Major 2015
Biomedical / Law 2015, 2016, 2017, 2018, 2019, 2020
Mechatronic Mid-Year 2016, 2017, 2018, 2019, 2020
Mechatronic/ Project Management 2019, 2020
Mechatronic 2015, 2016, 2017, 2018, 2019, 2020
Mechatronic / Arts 2016, 2017, 2018, 2019, 2020
Mechatronic / Commerce 2015, 2016, 2017, 2018, 2019, 2020
Mechatronic / Medical Science 2015, 2016, 2017
Mechatronic / Music Studies 2016, 2017
Mechatronic / Project Management 2015, 2016, 2017, 2018
Mechatronic / Science 2015, 2016, 2017, 2018, 2019, 2020
Mechatronic/Science (Health) 2018, 2019, 2020
Mechatronic / Law 2015, 2016, 2017, 2018, 2019, 2020
Mechatronic (Space) 2015
Mechatronic (Space) / Commerce 2015
Mechatronic (Space) / Medical Science 2015
Mechatronic (Space) / Project Management 2015
Mechatronic (Space) / Science 2015
Mechatronic (Space) / Law 2015
Mechatronic (till 2014) 2014
Mechatronic Engineering / Arts 2014
Mechatronic Engineering / Commerce 2013, 2014
Mechatronic Engineering / Medical Science 2013, 2014
Mechatronic Engineering / Project Management 2013, 2014
Mechatronic Engineering / Science 2013, 2014
Mechatronic (Space) (till 2014) 2014
Mechatronic Engineering (Space) / Arts 2014
Mechatronic Engineering (Space) / Commerce 2014
Mechatronic Engineering (Space) / Medical Science 2014, 2013
Mechatronic Engineering (Space) / Project Management 2013, 2014
Mechatronic Engineering (Space) / Science 2013, 2014
Mechatronic Engineering (Space) / Law 2014, 2013
Biomedical/Science (Medical Science Stream) 2018, 2019, 2020
Master of Engineering 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020
Master of Engineering (Mechanical) 2011, 2012
Master of Professional Engineering (Accelerated) (Biomedical) 2019, 2020
Master of Professional Engineering (Accelerated) (Mechanical) 2019, 2020
Master of Professional Engineering (Biomedical) 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020
Master of Professional Engineering (Mechanical) 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020
Mechatronic/Science (Medical Science Stream) 2018, 2019, 2020
Aeronautical Mid-Year 2019, 2020
Aeronautical/ Project Management 2019, 2020
Aeronautical 2019, 2020
Aeronautical / Arts 2019, 2020
Aeronautical / Law 2019, 2020
Mechanical Mid-Year 2019, 2020
Mechanical/ Project Management 2019, 2020
Mechanical 2019, 2020
Mechanical/Science (Medical Science Stream) 2018, 2019, 2020

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
(6) Communication and Inquiry/ Research (Level 3) Yes 10%
(7) Project and Team Skills (Level 3) Yes 0%
(5) Interdisciplinary, Inclusiveness, Influence (Level 4) No 0%
(4) Design (Level 4) Yes 4%
(2) Engineering/ IT Specialisation (Level 5) Yes 60%
(3) Problem Solving and Inventiveness (Level 4) No 26%
(1) Maths/ Science Methods and Tools (Level 4) Yes 0%

These goals are selected from Engineering & IT Graduate Outcomes Table 2018 which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table 2018 for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.